Does ESPN Understand Baseball?

This will sort of look like jumping on the (long-running) bandwagon, but ESPN continues to lose its luster, and this has become especially apparent now that the baseball season has started.

For starters, there is the sports network's seemingly infinite coverage of the NFL Draft, as if the NFL wasn't the only major sport out of season right now. Of course, they appear to be giving viewers what they want: a poll on SportsCenter revealed that fully half of ESPN viewers rated the NFL draft the most important event this coming weekend. Wow.

And it's not like those of us without the MLB network can simply stop watching ESPN: we need to see the highlights on Baseball Tonight. Even this show, despite Karl Ravech and the wonderful John Kruk, can be difficult to watch. Last night, Steve Phillips was ranting about Oliver Perez and the Mets, and the show also made a huge deal about the Pirates' sweep of the Marlins.

True, Perez's ERA thus far looks horrendous, and the Pirates' pitching has been terrific, and the Marlins were 11-1. Yet Perez's ERA is inflated mostly due to one bad outing, and when you play the Nationals for most of the first two weeks, as the Marlins did, your team record will be inflated beyond actual merit (not to take anything away from Pittsburgh).

With the plethora of wonderful baseball sites out there now (Fangraphs, Baseball Think Factory), watching Baseball Tonight becomes less pleasurable because they just don't seem to enlighten viewers much anymore. Do we really need a nightly Manny Ramirez update, or a fulsome focus on the new Yankees Stadium?

In the Long Run

In its nearly one-month existence, this site has mostly focused on elaborating on the basic ideas underlying the 'formula': Rules x Uncertainty x Interaction = Complex and Perpetually Novel Outcomes.

Necessarily, the first wave of posts offered brief overviews of the elements contained here, and probably gave short shrift to some key ideas. Thus, before moving on to more specific and no less important aspects of baseball's economic explanatory power, I just wanted to flesh out what I consider to be key ideas in economic affairs that we haven't adequately addressed. And here we see Uncertainty and Complex and Perpetually Novel Outcomes come together.

The notion that uncertainty plays a huge role in baseball and the economy (we've analogized this further to dark energy in the universe) is pretty straightforward, and it should be said that we don't really mean uncertainty in the basic sense that no one knows what will happen in the future. That's pretty obvious and not very insightful. (Again, though, I'm consistently surprised by economic writings that attempt to move, with little success, from description to prediction.)

We mean uncertainty in the sense that because so many things go into determining the outcome of one pitch or one play in baseball, our predictive power is limited no matter the statistical tools we have at our disposal. A new National Bureau of Economic Research working paper puts this succinctly: "Behavioral outcomes are influenced by hundreds of variables and a near-infinity of circumstances, happenstances, and coincidences." (Via Odd Numbers.) Because, at bottom, both baseball and economic activity involve human behavior, and because humans are (gloriously) imperfect, there is an endless array of things that will affect an outcome. The relatively new field of "neuroeconomics" takes this even a step further than behavioral economics.

Some readers might claim to find here somewhat of an inconsistency: we list Moneyball, after all, as one of our top book choices and isn't that all about greater statistical rigor in player evaluation? Surely we're not casting our lot with Joe Morgan and his anti-Moneyball crusade?

When I critique the utility (pun intended) of statistical models in economics, I am saying that because of the nearly infinite variety of factors that go into determining one individual decision let alone the course of a $13-trillion economy of 300 million people connected to the rest of the world, how can we hope to predict or manage anything? The approach of Moneyball, often distorted to on-base percentage and much-maligned as purely numerical, revolves around going beyond the traditional statistics used to measure player performance (like batting average) and trying to get a more complete picture of what players do that adds value to a team's effort. Simply sizing up a player's abilities (five tools, etc) or looking at batting average were seen to be insufficient. This won't be news to many readers.

But I would bet that Billy Beane and Bill James don't pretend that they can predict or micro-manage the on-field performance of teams and players. They try to raise the probability of certain outcomes and, ultimately, victory, but they know there are plenty of things (dark energy) out of their control. In this sense, all the noise in the financial press over the last two years about the Federal Reserve "engineering a soft landing" for the U.S. economy and the potential impact of the economic policies of the next president likely overstates things.

As an example, let's look at developments over the long-term, and this is where we see uncertainty working on a much larger scale of complex and perpetually novel outcomes. Let's take the entire course of a 162-game baseball season, and the American economy in the twentieth-century. (Disproportionate time scales, perhaps, but a useful way to think about it--you'll see.)

If you reran, as it were, an entire baseball season, it is highly unlikely that you would get the same result as before. The events as they actually turned out were only one possible pathway, not the only possible outcome. Anyone who has played Strat-O-Matic or Statis-Pro can tell you this and won't be particularly surprised by this observation. The developments during the 2008 season are not deterministic: the bounce of one batted ball, a close call at home, a quarter-inch difference in a pitch, a slight change in wind conditions. Any of these could alter a discrete outcome--compounded over 162 games, they could change the character of everything. We often here this expressed during a player's chase or .400. A few years ago wasn't it the case that with something like 16 more hits Barry Bonds would have hit .400? Put aside the steroids accusations and all the walks: sixteen more hits could easily have been attained with a few of the changes just mentioned--a different bounce, a fielder's position, etc.

Baseball is not Calvinistic: there is no predestination. Economic change, too, is not Calvinistic. If you reran the economic history of the twentieth century, nothing guarantees an exact replay of what happened in real life. Sure, we probably still would have ended up with mass production of automobiles, cell phones, and the Internet. But the dynamics of everything would likely be different. Detroit was not the foreordained geographic center of the auto industry. Other states and other countries were vying for that as well. 

Long-term economic change is often illustrated in economics textbooks by the Production Possibility Frontier, a curve that expands outward as outputs grow. This is a convenient way to depict aggregate economic growth, but doesn't really capture the developmental intricacies of how economic growth feels. Obviously, the point is to represent long-term change in an abstract manner free of potentially-distorting details. But that's like saying at the beginning of a baseball season: some teams will lose, some will win, there will be hits and strikeouts, and at the end there will be one champion. Well, yes that is what happens, but it doesn't really tell us anything about how. Here, in one sense, is an illustration of this. Look at the variety of developmental pathways and niches. Uncertainty and Complex and Perpetually Novel Outcomes are functions of each other.

OK, does this amount to anything more than an observation that contingency plays a large role in baseball and economics? The real payoff is in the implications. We should be careful about applying past lessons to future problems. I would be the first to say let's learn from history, but there's a difference between appealing directly to a past situation and looking instead at the general contours of what has gone before. In this sense, the contemporary debates about whether "Obamanomics" will be like "Clintonomics" or what JFK's tax cuts say about John McCain's economic policies really don't amount to anything meaningful.

We should be more appreciative, in the Popperian sense, of our ignorance: it opens up many more opportunities than a deterministic approach. This is one of the great lessons, for me at least, of David Halberstam's baseball history books: I am consistently surprised in reading them at the unexpected developments, the twists and turns that determined a crucial game or series in 1949 or 1964.

In the next set of posts, we'll begin to take on more specific aspects of baseball and the economy, including entrepreneurship, specialization, long-term dependency effects, and the element of time.

What Does this Site Do, Again?

Now that we have gone through the basic elements of our initial "formula," we can revisit the basic premise of this site and provide something of a wrap-up overview. There are still numerous items to discuss--extensions of the analogy, its limits, etc--but we thought it might be good at this point to restate the idea.

Theorizing in any discipline is about abstraction: you try to penetrate to the essential elements of something so as to understand it. This is what economists do: to get a handle on the complexity of economic activity, they seek the core characteristics (or, sometimes, laws)--supply and demand, marginal utility, revealed preference, etc.

In recent years, economists have expanded their purview beyond what we might see as "purely" economic elements. The book Freakonomics, for example, applied economic analysis to all manner of issues that were not traditionally seen as economic issues. But because economics is basically about human behavior and choice, it makes sense that economists would extend their disciplinary boundaries. I have certainly learned more from Steven Landsburg and Tim Harford than I ever did in a college macroeconomics course.

Our aim here is also abstraction, but hopefully in a more colloquial language: that of baseball. We're not saying that every single moment in a baseball game has its economic analogue, nor that every single economic situation has a parallel in baseball. (And we're happily open to reader suggestions for questions or interesting problems to explore.)

We're saying that when you boil down baseball--the on-field game, not the business of it, another growing topic in the past few years--to its essential elements, you get rules, uncertainty, interaction, and complex and perpetually novel outcomes. The same, we submit, is true of economic activity. Now, those seem rather obvious, especially if you simply think about them for a few minutes. But one thing that has surprised us as we have followed economic and financial discusions in the media and some of the academic literature is how remote those seem to be from what actually goes on in the economy.

Rules, of course, are mentioned all the time, as we constantly muse over economic laws and policies. Pick up any book or article written in the last few years on economic issues and you will undoubtedly find a sentence about an "age of uncertainty" or growing uncertainty as to the direction of the economy. Uncertainty is treated as something discrete, like a comet that passes by occasionally. Interaction is the dominant fact of human life in all facets but, until recently, seemed foreign in the economic literature. The steadily growing field of behavioral economics recognizes the importance of interaction, but still retains a focus on stand-alone individuals. Remember the charts from economics class, the business cycle and the production possibility frontier? Quite abstract, but they didn't really convey the dominant fact of economic activity: complex and perpetually novel outcomes. (One of our future posts will be a greater discussion of this, because it is so important.)

So there you have it: in our casting about for different ways to understand the economy, we hit upon baseball. There are probably a lot more people out there who understand at least the basics of baseball than could say they understand the economy and how it changes and develops. We're not experts, but we hope you share our growing understanding through baseball.

The Dynamic Composite of Teams and Economies

According to Martin Wolf, nations don't compete, companies do. Nevertheless, "American competitiveness" is much on the tongues of our cosmopolitan elite these days. The fear is that other countries, particularly China and India, are beginning to send the United States into an abyss of economic oblivion. This is quite redolent of the 1980s paranoia over Japan (when, I might add, members of that same Council on Competitiveness advocated American adoption of Japanese-style corporatism.)

Possibly the most frequently (over)used word in today's competitiveness conversations is "ecosystem"--what are the elements of an innovation ecosystem? How do we "architect" one? One of the most notable examples of this is a "Periodic Table of Innovation Elements" devised by ASTRA. It purports to list all of the, well, elements that are necessary to come together to form an economic ecosystem that is perpetually innovative. 

This is doubtlessly an innovative way to address competitiveness and economic policy. Unfortunately, it is also a bit misleading. Why? Well, let's see what baseball tells us!

One of the most fundamentally important questions that arises from our baseball analogy is, what explains the difference among teams and countries? If all baseball teams and national economies operate according to the underlying structure of rules, uncertainty, and interaction, why are some teams better than others and why do some countries grow wealthier than others? The answer lies not not only in the quality of players but also in the composite, the way the elements fit together.

Edmund Phelps, Nobel laureate in economics, has explained that a country's economic performance depends on both the strength of individual factors and its economic dynamism, the interlocking system of the relationships among those factors.

So that's obvious, right? We all know that Ernie Banks alone couldn't carry the Cubs to a championship. And isn't the Periodic Table of Innovation a way to express the elements together? Sort of. First, the analogy of the periodic table may be somewhat misleading; second, this reminds me of the Texas Rangers.

I already linked to this article, and I hate to confuse analogies, but we should be aware that the modern elements that make up the Periodic Table did not all appear at once. In fact, it seems that in the beginning there were only three. Trying to list all of the "elements" that make up an "innovation ecosystem" makes it seem like an organization (usually the government--ASTRA is a proponent of big-push federal initiatives) can simply step in and create de novo all these elements.

In 2000, the European Union announced its Lisbon Strategy, whereby it would spur innovation and entrepreneurship through heavy amounts of government-coordinated research and development. Obviously, R&D is critical to innovation. Economic dynamism, however, arises not necessarily from R&D or the generation of innovation, but from how a country makes innovation stick and build on itself.

In this way, the EU might be seen as the Texas Rangers of the international economy. For the past dozen years or so, the Rangers have poured nearly $100 million into big-name signings that translated into only four winning seasons. They haven't been able to put a consistently victorious team together, something that transcends individual players.

No one would argue that the New York Yankees' run of three consecutive World Series titles from 1998-2000 owed nothing to stellar players. But it remains disputed as to how to build such a dominant and consistent team, how to put the pieces together. The same applies to economic growth, and we shouldn't pretend that it is somehow akin to chemistry or physics (or what we think those disciplines are like), that we can simply build or "architect" growth.

Ha Ha Ha, Uncertainty, That's a Good One

Evidently, it is a long-standing joke among economists that uncertainty is a known unknown in economic models. At least early psychologists and modern neuroscientists recognize its importance: "It is, in short, the reinstatement of the vague to its proper place in our mental life which I am so anxious to press on the attention."

That is somewhat reminiscent of my earlier-expressed view that uncertainty is sort of like the dark matter of the economic universe. (Or, I guess more accurately today, dark energy.) And that, I admit, should have prompted me to recall the famous Donald Rumsfeld "poetry" about "unknown unknowns."

Correction

I stand corrected: thank you to reader skmurphy for pointing out my erroneous attribution of the Game of Life to von Neumann, when it was actually developed (on the back, admittedly, of Neumann's work) by John Conway. I had cited Warsh's cite, and also recalled from Waldrop's book, that Neumann was involved. Error duly noted and corrected. Thanks.

What are Complex and Perpetually Novel Outcomes?

So, at long last, we come to the product of our initial formula. As a refresher, let's recall that formula:

Rules x Action in the face of Uncertainty x Interaction = Complex and Perpetually Novel Outcomes

(It should be apparent to most readers by now that this "formula" is slightly tongue-in-cheek. We'll explore that in a future post.)

What do we mean by "complex and perpetually novel"? Let's start with complex, and let me first say what I don't mean by complex. I don't mean the increasing complexity of, say, tying a shoelace knot. You start out with simplicity, you do a loop, you do another loop, more loops at random, until you're left with a knot of such Gordian proportions that you simply take off the shoe. I don't mean that type of complexity. 

I also don't mean the complexity of Calvinball, the game made up and continuously changed by Calvin and Hobbes. With no fixed rules, and the unpredictability of a new rule at any time, the game was immediately complex--impenetrable to even Calvin and Hobbes, generating plenty of frustration and fisticuffs.

What I mean by complexity is that, in any system with a finite and (relatively) immutable set of rules and actions, the number of possible outcomes far exceeds that which you would expect from the seemingly simple starting point. A light bulb flickered on for Peter Albin, an economic pioneer in the field of complexity, when he ran across the "game of Life" created by the brilliant John von Neumann to illustrate cellular automata theory. Here's Albin, as quoted by David Warsh: "What struck me was that in working with automata that derived from 'Life,' a very few operating principles generated model behavior which seemed to be as interesting as those produced by quite massive constructions." (Emphasis added.)

That appears to be quite an apt description of baseball in its essence. In baseball, there's really a limited number of actions you can take in any given situation. The pitcher delivers; the batter can swing or take; the fielders either make the play or it's a hit; the runners go or stay. There are always three outs. Runs score. Games end. (I'll obligingly note the worn but ever-insightful observation that, theoretically, a baseball game could never end: it's not necessarily temporally confined like other sports.)

OK, that's the "complex" part of the product. What about "perpetually novel"? This one is easier. Many of you are likely familiar with Tim Kurkjian's regular feature on "Baseball Tonight," in which he gleefully notes all the things that happened in baseball over the past week that had never, ever happened before. On first impression, it may be surprising that new outcomes could consistently happen in a game with a finite number of rules and possible actions. But if you think about all the elements that go into creating an outcome--the rules, the uncertainty, the interactions--it's not so surprising, after all.

What we find, furthermore, is a close connection between complexity (in our sense here) and perpetually novel outcomes. Here, for example, is Warsh, on his view of economic complexity: "My own sense of the meaning of the word had derived from the use of the word complexity in a famous paper by the economist Allyn Young (“Increasing Returns and Economic Progress”) to describe the growing variety of goods and services, their apparently ever-increasing specialization and differentiation, what we mean today by the supremely hazy term “development."'

Some perceptive readers will at this point likely notice the debt that this site owes to complexity theory (or chaos theory or whatever you want to label it). And while it's true that the ideas behind Box Score were semi-inspired by complexity and ideas related to it (including some of the books listed on this site), that's only part of the story.

Let's face it: complexity theory is sometimes really hard to understand. Most of us, if we're seeking different ways to understand the economy or if we're just trying to get a grasp on basic concepts, are not going to learn all the terminology of a new branch of science. So we at Box Score searched for a simpler way to understand things: a system that generated complexity but that most people could understand. Voila: baseball.